Design and operate core AI platform components for training, deploying, and serving ML models at scale.
Own model serving and inference workflows end-to-end, optimizing for reliability, latency, throughput, and cost.
Collaborate with product, infrastructure, and security teams to build scalable platform capabilities for AI-powered features.
Mozilla Corporation is the non-profit-backed technology company behind Firefox and Pocket, with over 225 million monthly users. A wholly-owned subsidiary of the Mozilla Foundation, the company is mission-driven, employee-owned, and focused on privacy and open standards.
Design, build, and deploy AI/ML solutions from prototype to production for client business problems.
Apply generative AI and LLMs, establishing MLOps best practices including CI/CD and model monitoring.
Serve as a trusted technical advisor, translating ambiguous problems into well-scoped solutions and presenting to stakeholders.
DevIQ builds modern cloud and data solutions for mid-market companies focused on energy reduction, healthcare, education, and smart cities. The company offers competitive benefits, a strong team culture, and opportunities to work on end-to-end solutions with multi-disciplinary teams.
Design and build systems that improve the efficiency of ML training and inference workloads.
Develop tooling that helps ML engineers debug, profile, optimize, and monitor model performance.
Partner with ML researchers and product teams to identify bottlenecks and drive performance improvements.
Reddit is a community of communities built on shared interests, passion, and trust, hosting the most open and authentic conversations on the internet. With over 100,000 active communities and approximately 126 million daily active users, Reddit is one of the internet's largest sources of information.
Build and operate the real-time inference service for the risk decision engine with low latency and high availability.
Own model deployment infrastructure including CI/CD, shadow mode, and staged rollouts.
Build model observability and partner with Risk Data Science for production operation.
Mercury is a fintech company that provides banking services for startups via partner banks. The company is committed to creating a safe environment and values diversity, with a growing team focused on innovation.
Take ownership of the ML API serving NBA recommendations and harden it for low-latency production traffic.
Ship your first agent tool contract end-to-end: schema design, handler implementation, and unit tests.
Set up the eval foundation for agents with golden transcripts, rubric-based judges, and regression suites.
Clutch is a vertical SaaS company backed by Andreessen Horowitz that helps credit unions become fintech lenders, providing affordable lending solutions to over 130 million Americans. The team is small, ambitious, and shipping fast with a culture that values pragmatism and real autonomy.
Design and build scalable ML training, deployment, and inference pipelines using CI/CD and cloud infrastructure.
Implement MLOps for model versioning, monitoring, and automated retraining to detect drift and performance degradation.
Partner with Data Scientists and Product teams to productionise models and integrate ML into customer-facing products.
We develop solutions that make an impact for companies around the globe. Our culture embraces openness, acts with respect, shows grit & guts, and combines employment with enjoyment.
Design, train, evaluate, and ship ML systems for governance and security, starting with prompt injection detection and behavioral anomaly detection.
Build supporting infrastructure including data pipelines, feature stores, model serving, and evaluation harnesses.
Set technical direction for ML work, own architecture, evaluation methodology, and model lifecycle.
Docker provides developer tools for building, sharing, and running applications across Docker Desktop, Docker Hub, and Docker Scout. With over 20 million monthly users and a globally distributed remote-first team, Docker is trusted by solo founders to the world's largest companies.
Own the technical design and delivery of subsystems in a high-throughput, low-latency inference platform.
Develop robust API layers and SDKs that abstract complex distributed inference orchestration.
Build and harden a multi-tenant control plane for metering, rate limiting, and tenant isolation.
Stack develops revolutionary AI and autonomous systems to enhance safety and efficiency in trucking. The team has decades of experience deploying real-world systems and is committed to inclusion, entrepreneurship, and innovation.
Design, develop, test, and deploy AI/ML models and applications including NLP pipelines, predictive models, recommendation engines, and intelligent automation workflows.
Build and integrate large language model (LLM) powered features using APIs such as OpenAI, Azure OpenAI, or Anthropic; implement retrieval-augmented generation (RAG) patterns and AI agent workflows.
Develop and maintain data pipelines that support model training, fine-tuning, evaluation, and real-time or batch inference.
ExtensisHR is a Professional Employer Organization (PEO) in the U.S. with client employees in all fifty states. They deliver personalized HR services for HR, employee benefits, payroll and taxes, employer risk, compliance, and employee management.
Design, develop, and deploy AI/ML models to automate and improve internal workflow.
Build and maintain ML pipelines within an AWS cloud environment.
Integrate ML capabilities into existing Java and React application workflows.
Oddball aims to improve daily lives by delivering quality software to the federal space. With a team of experienced engineering, product, and UX professionals, we value learning, growth, and making a big impact in a rapidly growing company.